Cardiac output and leg and arm blood flow during incremental exercise to exhaustion on the cycle ergometer
Bibliographic record
Abstract
To determine central and peripheral hemodynamic responses to upright leg cycling exercise, nine physically active men underwent measurements of arterial blood pressure and gases, as well as femoral and subclavian vein blood flows and gases during incremental exercise to exhaustion (Wmax). Cardiac output (CO) and leg blood flow (BF) increased in parallel with exercise intensity. In contrast, arm BF remained at 0.8 l/min during submaximal exercise, increasing to 1.2 +/- 0.2 l/min at maximal exercise (P < 0.05) when arm O(2) extraction reached 73 +/- 3%. The leg received a greater percentage of the CO with exercise intensity, reaching a value close to 70% at 64% of Wmax, which was maintained until exhaustion. The percentage of CO perfusing the trunk decreased with exercise intensity to 21% at Wmax, i.e., to approximately 5.5 l/min. For a given local Vo(2), leg vascular conductance (VC) was five- to sixfold higher than arm VC, despite marked hemoglobin deoxygenation in the subclavian vein. At peak exercise, arm VC was not significantly different than at rest. Leg Vo(2) represented approximately 84% of the whole body Vo(2) at intensities ranging from 38 to 100% of Wmax. Arm Vo(2) contributed between 7 and 10% to the whole body Vo(2). From 20 to 100% of Wmax, the trunk Vo(2) (including the gluteus muscles) represented between 14 and 15% of the whole body Vo(2). In summary, vasoconstrictor signals efficiently oppose the vasodilatory metabolites in the arms, suggesting that during whole body exercise in the upright position blood flow is differentially regulated in the upper and lower extremities.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".